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cls_10_backbone_100k
ttqdunggg/cls_10_backbone_100k
cls_10_backbone_100k is a machine learning model from ttqdunggg. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as agpl-3.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- agpl-3.0
- Model type
- roberta
- Access
- Public
- Created
- Nov 11, 2025
- Updated
- Nov 11, 2025
- SHA
- aba2812b
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
cls_10_backbone_100k
This model is a fine-tuned version of RonTon05/model_content_V2_test on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6452
- Accuracy: 0.8056
- F1: 0.7586
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.3593 | 1.0 | 276 | 0.8976 | 0.7355 | 0.5410 |
| 0.7192 | 2.0 | 552 | 0.6962 | 0.7938 | 0.7123 |
| 0.5185 | 3.0 | 828 | 0.6655 | 0.8027 | 0.7329 |
| 0.4006 | 4.0 | 1104 | 0.6541 | 0.8077 | 0.7655 |
| 0.3281 | 5.0 | 1380 | 0.6452 | 0.8056 | 0.7586 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1
- Library
- transformers
- Type
- roberta
- License
- agpl-3.0
- Created
- Nov 11, 2025
- Updated
- Nov 11, 2025